(25 Aug 2019) Science, engineering and technology

Recently, we had a very enthusiastic and excited bunch of undergraduate students from Mumbai visiting us at Venture Center, Pune. They were pursuing degrees in Biotechnology. In their introductions, some said they were doing a Bachelor of Science in Biotechnology while others said that they were pursing a Bachelor of Engineering in Biotechnology.  I decided to pick on that theme to discuss with them and explore what they understood by those terminologies — Science, Engineering and Technology!  Was there any difference between the degrees that they were pursuing or was it just a matter of words? (I do realise that several universities in India carelessly name degree programs based on what say AICTE will allow etc rather than truly structure the program to fit the name or -vice versa- chose the name that fits the program design.)  I feel that students should be aware of what their degrees mean. So here is my attempt at clarifying the nomenclature —

 A disclaimer — degrees and tags mean nothing eventually; they merely indicate a certain type of training and orientation. Everybody can change their training and orientation at any time in their careers or have multiple orientations.


People trained in “Science” are trained in the “Scientific Method” — a certain systematic way of constructing a view (theory) of the world based on experiments and known facts. ( I will not get into the Scientific Method here.) Scientists are explorers and discoverers of new knowledge. They do not necessarily want to design or control the world around them. They will explore the world with curiosity, try and build understanding of the phenomenon and wish to share that new knowledge with everybody. Scientists are explorers who discover new knowledge!


People trained in engineering are trained to develop mastery (in the sense of being able to design, control, optimise etc) over complex systems (like machines, factories, computers, electronic equipment, bridges, dams, aeroplanes, now even cells and tissues etc). Engineers are taught to develop quantitative understanding of systems, equipped with tools to model and analyse such systems, and therefore be able to design, predict and control the behaviour of such systems. Engineers are “masters” of complex systems and their behaviour!


You will note the difference immediately if you think of say flying on an aeroplane. You do so with confidence because you think that there are people who have designed it with care, have thought through various possibilities and planned for it, have put in place measurements and control systems etc. That is to say, you know engineers have been at work ensuring the system works with reliability.  Imagine yourself agreeing to fly on an aeroplane made by a scientist (who is keen to experiment and learn new things all the time) — very unlikely !!   Actually, engineers need to make their systems very very predictable and thus boring — and this turns off scientists!  (I find this amusing!)

Similarly, engineers can find the elegant simplicity that physicists strive for or the chaos in which biologists operate very unsettling!  Scientists are at ease exploring the world around — with all its “chaos” — and teasing out facts and insights.


Technology is an entirely different thing. Technology is all about problem solving. This is a different orientation and may often need a different training. Somebody, somewhere at some point has a problem or a need that needs to be solved. A scientist or engineer may have explored the problem (such as a disease for ex) and discover new ways to tackle it.  Somebody, somewhere and at some point has tools to address the problem. A technologist wants to solve the problem, is resourceful in finding the tools he/ she needs, sees the connect and acts to demonstrate a solution.

Scientists discover the world around you, Engineers design and control the world around you and Technologists build the world around you.

You will note that there can be scientists who are excellent technologists or engineers who also excel as scientists and so on. Boundaries exist only to the extent you allow them to exist.

So coming back to the young Biotechnology students from Mumbai —- if their degrees reflect what they learn, one could probably say that:

  • All of them were studying Biotechnology. So they are focussing on learning to solve problems using living systems (bio) or in living systems (bio). For example, producing a biopharmaceutical molecule using cell lines and bioreactors.
  • The folks studying towards a science degree are probably learning how to discover new insights and knowledge about living systems that can be useful for biotechnology. For example, discovering pathways in cell lines that influence the yield of a certain biopharmaceutical product.
  • The folks studying towards a engineering degree are hopefully learning how to design, predict and control living systems that can be useful for biotechnology. For example, being able to quantitatively design a bioreactor, predict how the reactor will perform under different conditions and situations, predict yield and control the system if it does not perform as required.

Some personal opinions and hypothesis:

  • You will note that the ability to design, predict and control gives a certain advantage to “engineers” in incremental innovation.
  • The fact that “scientists” are first to reach new knowledge, gives scientists an edge or a lead in path changing or radical innovation.
  • The fact that most large organisations today are complex systems, I believe that an engineering training is a better preparation for managing larger organizations. One often needs to put predictable and reliable processes and systems in place in large organisations and not keep experimenting with ad hoc ideas — something that engineers (in orientation)  probably understand better than scientists (in orientation).


(2 Sep 2019) Disruptive innovation at the interfaces of the drug industry

Guest Editorial: Disruptive innovation at the interfaces of the drug industry
(Journal: Indian Drugs, Aug 2019 issue)

Link: https://www.indiandrugsonline.org/issuesarticle-details?id=OTU5

Dear Reader,

I am delighted to contribute this Guest Editorial for the current issue of Indian Drugs. I was very happy to interact with industry leaders at the Indian Drugs Annual Day 2019 and share some of our learning on innovation and entrepreneurship in medical products. In this Guest Editorial, I wish to focus on how innovation at the interface of the drug industry and other industries serving the healthcare market will shape the drug industry in the future.

The drug industry is a supplier of solutions for the global health market. There are many other industries that serve this health market as well – other therapeutics, devices, diagnostics, nutraceuticals, preventives, sanitation and hygiene, delivery health care and diagnostic services, digital systems in health, healthcare financing etc. In the past, the drug industry could afford to operate in a silo, but it is clear that the future of serving the health market lies in blurring boundaries between various industry sectors and in finding value creation opportunities at the interface of industry sectors rather than operating in silos.

One can already see how IT and mobile computing is transforming the pharmaceuticals marketing, sales and distribution channels. In the last decade, the largest Venture Capital investments in India were reserved for IT enabled platforms in healthcare delivery and pharmaceutical distribution. While the initial focus of these startups is on drugs and medical services, it is clear that their sights are set much higher — on a future of integrated product and service delivery platforms with platform loyalty and patient/ user/ customer data being the key value creators. (This is akin to the early days of Flipkart or Amazon starting with books and expanding to many other domains. Today, the data they own is invaluable.)

The drug industry will be immediately recognize how IOT (Internet of Things), data analytics, cloud computing and mathematical models (including AI/ML) is going to transform production environments (ex: continuous manufacturing), regulatory compliance requirements (ex:  live data and continuous audits) and clinical trials tracking and in-use performance monitoring. Wearable diagnostics and technical textiles promise the change the way health is monitored, medication decisions are taken by clinicians and how drug performance is quantified and observed. Recent advances in novel sensors and diagnostics (such as the ingestible pill sensors) will have a deep influence on formulation design and drug delivery systems.

The interface between diagnostics and therapeutics is again blurring as innovators try to build a closed loop between health parameter measurements and therapy (say, for example, glucose measurements and insulin delivery). Similarly, many innovators are exploring opportunities at the interface of medical devices and therapeutics; for example, implants that also control local infection/ inflammation or drug eluting stents.

Yet another mega-trend is the transition towards precision and personalized medicine. So far, the largest hindrances to personalized medicine were lack of personalized data and data trends, methods to conveniently and accurately capture data, the inability to handle large, varied and fuzzy data sets, and convenient correlational models for multi-parameter population-wide analysis. But this is set to change. Imagine, for example, a population of iWatch (that tracks cardiac performance) users who also allow tracking of data on their physical activities (say, with a FitBit), nutritional information, other medical and diagnostics reports, medication and drugs purchase data etc. This data set could possibly be mined for trends and correlations and captured in the form of a ML algorithm which could then be used predict actual or potential conditions for a given person and may be even suggest personalized guidance and therapy. In such a scenario, the implications for the drug industry are large and extensive.

The drug discovery process (as practiced currently) is just too cumbersome, cost intensive and risky, and therefore has become hegemony of a few who can afford to take such risks.  It is clearly a broken process that is awaiting a disruption. Just as Elon Musk and SpaceX have turned the expensive space industry on its head by demonstrating reusable rockets, the drug industry is waiting for an innovation that will transform the drug discovery process entirely and thus make it more accessible and productive. India has tried new ideas like the Open Source Drug Discovery or Reverse Pharmacology approaches in the past. New ideas like the MANAV-Atlas program of DBT also hold considerable promise for leads. It is my opinion that the advances in biological engineering which aim to apply engineering principles and math modeling to living systems combined with the emerging capabilities in data handling and computing are probably going to increase productivity in drug discovery in significant ways.

In conclusion, it is important for the drug industry to rise above narrow industry boundaries, get comfortable with blurring interfaces and focus on the ultimate goal of address issues of health. It is time that the Indian Drug Manufacturing association organize task forces to discuss, research, foresee and understand how new technologies will impact and transform the drug industry and what actions the industry can take to remain relevant.

V. Premnath, PhD
Head, NCL Innovations & Director, Venture Center
CSIR-National Chemical Laboratory, Pune

About the Guest Editor

Dr V. Premnath is currently the Head, NCL Innovations – the group within National Chemical Laboratory (NCL) charged with the responsibility of championing the cause of technology innovation within NCL. Dr Premnath is also the Director of the Venture Center – a technology business incubator on NCL campus. Dr Premnath is also a Scientist, Polymer Science & Engineering Division at NCL with an interest in technology development for medical products.

Dr. V. Premnath holds a B.Tech. from the Indian Institute of Technology – Bombay and a Ph.D. from the Massachusetts Institute of Technology, USA. He has also been a Chevening Technology Enterprise Fellow with the Centre for Scientific Enterprises, London Business School and Cambridge University, UK. Dr Premnath’s experience with medical products development is focused on polymeric implants and has resulted in two families of commercial products and two startups.

(22 May 2019) Lessons from Sweden in Innovation Management

My Linkedin Articles on my Sweden Tour:

Sting and Propel Capital: Example of an angle investment activity coordinated by an incubator
KTH’s Innovation Readiness Levels
Astra Zeneca BioVenture Hub: An example of open innovation by a corporate
Why does Sweden do so well in innovation and entrepreneurship?